Compare Regression

library(png)
library(readxl)
library(knitr)
library(cowplot)
library(ggplot2)
library(magick)
source('C:/Users/Sylvia/Dropbox (Partners HealthCare)/Sylvia_Romanos/scRNASeq/Code/Functions.R')

Get File Paths

folder_base <- 'C:/Users/Sylvia/Dropbox (Partners HealthCare)/Sylvia_Romanos/scRNASeq/Code/Output/'
filename_sampleParam <- 'C:/Users/Sylvia/Dropbox (Partners HealthCare)/Sylvia_Romanos/scRNASeq/Data/sample_parameters.xlsx'
sampleParam <- read_excel(filename_sampleParam)
filename_metaData <- 'C:/Users/Sylvia/Dropbox (Partners HealthCare)/Sylvia_Romanos/scRNASeq/Data/Dexa_meta.xlsx'
metaData <- read_excel(filename_metaData)

sample_name <- metaData$Sample[31]
filter = TRUE

regress_TF = FALSE
folder_noregress = makeFolders(folder_base,sample_name,filter,regress_TF, FALSE)
regress_TF = TRUE
folder_regress = makeFolders(folder_base,sample_name,filter,regress_TF, FALSE)
#parameters = read.csv(file=paste0(folder_regress,'parameters.csv'), sep=",")

# Load data
filename_metaData <- 'C:/Users/Sylvia/Dropbox (Partners HealthCare)/Sylvia_Romanos/scRNASeq/Data/Dexa_meta.xlsx'
filename_sampleParam <- 'C:/Users/Sylvia/Dropbox (Partners HealthCare)/Sylvia_Romanos/scRNASeq/Data/sample_parameters.xlsx'
metaData <- read_excel(filename_metaData)

sampleParam <- read_excel(filename_sampleParam)

    

print(parameters)

print(paste0('Sample: ',sample_name))

[1] "Sample: GL1369PB"

print(paste0('Folder Filter: ',folder_regress))

[1] "Folder Filter: C:/Users/Sylvia/Dropbox (Partners HealthCare)/Sylvia_Romanos/scRNASeq/Code/Output/GL1369PB/Filtered/Regress/"

QC

# PCA
pathName_scatter1 <- paste0(folder_noregress,'QC Metrics/scatter.png')
pathName_scatter2 <- paste0(folder_regress,'QC Metrics/scatter.png')

pathName_violin1 <- paste0(folder_noregress,'QC Metrics/violin.png')
pathName_violin2 <- paste0(folder_regress,'QC Metrics/violin.png')

include_graphics((pathName_scatter1))

include_graphics((pathName_violin1))

#include_graphics(c(pathName_violin1,pathName_violin2))

#1 <- ggdraw() + draw_image(pathName_violin1, scale = 1.2)
#p2 <- ggdraw() + draw_image(pathName_violin2, scale = 1.2)
#plot_grid(p1, p2)

PCA

# PCA
PCA_dim<- sampleParam$PCA_dim[sampleParam['Sample'] == sample_name]
print(paste0('PCA_dim: ',PCA_dim))

[1] "PCA_dim: 15"

pathName_filter1 <- paste0(folder_regress,'PCA/Elbow.png')
pathName_filter2 <- paste0(folder_regress,'PCA/DimLoading.png')
pathName_filter3 <- paste0(folder_regress,'PCA/DimHeatMap1_6.png')
pathName_filter4 <- paste0(folder_regress,'PCA/DimHeatMap7_12.png')

pathName_nofilter1 <- paste0(folder_noregress,'PCA/Elbow.png')
pathName_nofilter2 <- paste0(folder_noregress,'PCA/DimLoading.png')
pathName_nofilter3 <- paste0(folder_noregress,'PCA/DimHeatMap1_6.png')
pathName_nofilter4 <- paste0(folder_noregress,'PCA/DimHeatMap7_12.png')

p1 <- ggdraw() + draw_image(pathName_filter2, scale = 1)
p2 <- ggdraw() + draw_image(pathName_nofilter2, scale = 1)
plot_grid(p1, p2)

include_graphics(c(pathName_filter3,pathName_nofilter3))

include_graphics(c(pathName_filter4,pathName_nofilter4))

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PCA Individual Plots

pathlist =  vector()
for (x in 1:(PCA_dim -1)){
  y <- x+1
  pathName_nofilter <- paste0(folder_noregress,'PCA/PCA',x,'_',y,'.png')
  pathName_filter <- paste0(folder_regress,'PCA/PCA',x,'_',y,'.png')

  p1 <- ggdraw() + draw_image(pathName_nofilter, scale = 1)
  p2 <- ggdraw() + draw_image(pathName_filter, scale = 1)
  print(plot_grid(p1, p2))
}

Cluster Metrics

resolution_val<- sampleParam$resolution_val[sampleParam['Sample'] == sample_name]
print(paste0('Resolution: ',resolution_val))

[1] "Resolution: 1"

pathName_nofilter <- paste0(folder_noregress,paste0('Cluster/ClusterMetrics','.png'))
pathName_filter <- paste0(folder_regress,paste0('Cluster/ClusterMetrics','.png'))

p1 <- ggdraw() + draw_image(pathName_nofilter, scale = 1)
p2 <- ggdraw() + draw_image(pathName_filter, scale = 1)
print(plot_grid(p1, p2))

Cluster with Umap

resolution_val<- sampleParam$resolution_val[sampleParam['Sample'] == sample_name]
print(paste0('Resolution: ',resolution_val))

[1] "Resolution: 1"

pathName1_nofilter <- paste0(folder_noregress,paste0('Cluster/ClusterUmap',resolution_val,'.png'))
pathName1_filter <- paste0(folder_regress,paste0('Cluster/ClusterUmap',resolution_val,'.png'))

pathName2_nofilter <- paste0(folder_noregress,paste0('Cluster/HeatMap',resolution_val,'.png'))
pathName2_filter <- paste0(folder_regress,paste0('Cluster/HeatMap',resolution_val,'.png'))


p1 <- ggdraw() + draw_image(pathName1_nofilter, scale = 1)
p2 <- ggdraw() + draw_image(pathName1_filter, scale = 1)
print(plot_grid(p1, p2))

p1 <- ggdraw() + draw_image(pathName2_nofilter, scale = 1)
p2 <- ggdraw() + draw_image(pathName2_filter, scale = 1)

Error in magick_image_readpath(enc2native(path), density, depth, strip) : 
  Magick: UnableToOpenBlob `C:\Users\Sylvia\Dropbox (Partners HealthCare)\Sylvia_Romanos\scRNASeq\Code\Output\GL1369PB\Filtered\Regress\Cluster\HeatMap1.png': No such file or directory @ error/blob.c/OpenBlob/2701

Cell Labeling

pathName_nofilter <- paste0(folder_noregress,paste0('Cell Type/'))
cell_images_nofilter<-list.files(pathName_nofilter, pattern = ".png", full.names = TRUE)

pathName_filter <- paste0(folder_regress,paste0('Cell Type/'))
cell_image_filter<-list.files(pathName_filter, pattern = ".png", full.names = TRUE)


for (x in 1:length(cell_images_nofilter)){
  p1 <- ggdraw() + draw_image((cell_images_nofilter[x]), scale = 1)
  p2 <- ggdraw() + draw_image((cell_image_filter[x]), scale = 1)
  print(plot_grid(p1, p2))

  #print(include_graphics(x))
}

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